Polarization on Twitter during the COVID-19 crisis: Caso Aislado and Periodista Digital

Authors

DOI:

https://doi.org/10.26441/RC20.2-2021-A2

Keywords:

monetization, twitter, bot, caso aislado, periodista digital, influencer, alarm

Abstract

The announcement of the State of Alarm in Spain in March 2020 brought with it a period of great information intensity in traditional and digital media. The extraordinary nature of the measure, which provided the Government with exceptional measures to confront the Covid-19 pandemic, gave rise to a tremendously polarized scenario. In this context, some webs known for the dissemination of disinformation campaigns and, even, the promotion of ideas closes to the alt-right, were especially active in networks promoting the dissemination of ideological content with the aim of capturing traffic for subsequent monetization through advertising. This work follows the activity around of two of these webs on Twitter, Caso Aislado and Periodista Digital, with the intention of determinate their role in the political polarization. For more than two months, more than 100,000 tweets were captured, stored and studied using R software and various analysis algorithms to determine their social activity, the possible presence or not of bots or automated profiles, the nature of the content and the emotional charge associated with it. There is an intense organized activity around both portals through a high percentage of apparently automated accounts and the support of influencers profiles. Although with differences inherent around each web, it is possible to glimpse an intentional coordination through campaigns that combine content, use of support accounts and automations.

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Author Biographies

Sergio Arce García, Universidad Internacional de La Rioja

Doctor Cum Laude y Premio Extraordinario de Doctorado en Humanidades y Comunicación por la Universidad de Burgos. Profesor Contratado Doctor en la Universidad Internacional de La Rioja (UNIR), con un sexenio de investigación. Investigador del grupo COYSODI de UNIR sobre comunicación y sociedad digital. Sus líneas de investigación se centran en el análisis masivo de medios de comunicación y redes sociales.

Fátima Vila Márquez, Universitat de Barcelona

Doctora Cum Laude y Premio Extraordinario de Doctorado por la Universidad Complutense de Madrid, Master en Marketing Online Internacional por la Escola Superior de Comerç - ESCI Pompeu Fabra y Experta en Comunicación Corporativa y Propaganda Política por la Universidad de Sevilla. Profesora en Universitat de Barcelona, EAE Business School (Universidad Politécnica de Barcelona) y Ostelea (Universitat de Lleida) donde dirige varios programas de máster. Es consultora de comunicación y contenidos digitales en Nora&Pierre Content LAB.

Joan Francesc Fondevila i Gascón, Blanquerna-Universitat Ramon Llull

Doctor Cum Laude y Premio Extraordinario de Doctorado por la Universitat Autònoma de Barcelona. Profesor titular Aneca y profesor agregado AQU en Blanquerna-Universitat Ramon Llull, Escola Universitària Mediterrani-Universitat de Girona, Universitat Pompeu Fabra, Cesine, Euncet y EAE Business School-Universitat Politècnica de Catalunya. Cuatro sexenios de investigación. IP del Grupo de Investigación sobre Sistemas Innovadores de Monetización en Periodismo y Marketing Digital (SIMPED) y del Grupo de Investigación sobre Periodismo Digital y Banda Ancha. Autor del blog científico http://www.telecomunicacionesyperiodismo.com. Director del Centro de Estudios sobre el Cable (CECABLE). Numerosos premios ganados en investigación, docencia y gestión.

References

Ahmed, W., Vidal-Alaball, J., Downing, J. y López Seguí, F. (2020). COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data. Journal of Medical Internet Research, 22(5), e19458. https://doi.org/10.2196/19458 DOI: https://doi.org/10.2196/19458

Arce García, S., Orviz Martínez, N. y Cuervo Carabel, T. (2020). Impacto de las emociones vertidas por diarios digitales españoles. El Profesional de la Información, 29(5). DOI: https://doi.org/10.3145/epi.2020.sep.20

Asociación de la Prensa de Madrid (27 de julio de 2014). Periodistadigital.com y su director vulneraron el código deontológico en una noticia sobre una mujer víctima de secuestro y violación. Federación de Asociaciones de Periodistas de España (FAPE). https://bit.ly/3iQgj0M

Auxier, B.E. y Vitak, J. (2019). Factors Motivating Customization and Echo Chamber Creation Within Digital News Environments. Social Media + Society, 5(2), 205630511984750. https://doi.org/10.1177/2056305119847506 DOI: https://doi.org/10.1177/2056305119847506

Bakir, V. y Mcstay, A. (2017). Fake News and The Economy of Emotions. Digital Journalism, 6(2), 154-175. DOI: https://doi.org/10.1080/21670811.2017.1345645

Bastian, M.; Heymann, S. y Jacomy, M. (2009). Gephi: An Open Source Software for Exploring and Manipulating Networks. En Proceedings of the Third International ICWSM Conference, 17-20 de mayo, San Jose: California. DOI: https://doi.org/10.1609/icwsm.v3i1.13937

Becerra, M. (2016). Revolución digital: una introducción. Entre la crisis y sostenibilidad. Revista Mexicana de Comunicación, 1(139), 64-69.

Bell, E. J., Owen, T., Brown, P.D., Hauka, C. y Rashidian, N. (2017). The Platform Press: How Silicon Valley Reengineered Journalism. Tow Center, Columbia Journalism School. https://bit.ly/3l1484a

Blondel, V., Guillaume, J., Lambiotte, R. y Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 10. https://doi.org/10.1088/1742-5468/2008/10/P10008 DOI: https://doi.org/10.1088/1742-5468/2008/10/P10008

Calvo, E., Aruguete, N. (2020). Fake news, trolls y otros encantos. Cómo funcionan (para bien y para mal) las redes sociales. Siglo XXI Editores.

Campos Freire, F. (2008). Las redes sociales trastocan los modelos de los medios de comunicación tradicionales. Revista Latina de Comunicación Social, 63, 287-293. https://doi.org/10.4185/RLCS-63-2008-767-287-293 DOI: https://doi.org/10.4185/RLCS-63-2008-767-287-293

Cid, G. (05 de mayo, 2020). 1M de clics al mes por cabrearte: las webs de desinformación se disparan con el covid. El Confidencial. https://bit.ly/375saT8

Comisión Europea (2018). A multi-dimensional approach to disinformation. Report of the independent high level group on fake news and online disinformation. Luxembourg: Publications Office of the European Union.

Evolvi, G. (2017). #Islamexit: inter-group antagonism on Twitter. Information, Communication & Society, 22(3), 386-401. https://doi.org/10.1080/1369118x.2017.1388427 DOI: https://doi.org/10.1080/1369118X.2017.1388427

Freelon, D., Bossetta, M., Wells, C., Lukito, J., Xia, Y. y Adams, K. (2020). Black Trolls Matter: Racial and Ideological Asymmetries in Social Media Disinformation. Social Science Computer Review, 089443932091485. https://doi.org/10.1177/0894439320914853 DOI: https://doi.org/10.1177/0894439320914853

Frischlisch, L., Klapproth, J. y Brinkschulte, F. (2019). Between Mainstream and Alternative – Co-orientation in Right-Wing Populist Alternative News Media. En First Multidisciplinary International Symposium, MISDOOM 2019. Hamburg, Germany, February 27 – March 1, 2019. https://link.springer.com/book/10.1007/978-3-030-39627-5

Glenski, M., Weninger, T. y Volkova, S. (2018) Propagation From Deceptive News Sources Who Shares, How Much, How Evenly, and How Quickly?. IEEE Transactions on Computational Social Systems, 5(4), 1071-1082. https://doi.org/10.1109/TCSS.2018.2881071 DOI: https://doi.org/10.1109/TCSS.2018.2881071

Goyanes Martínez, M. (2012). Monetizar el periodismo digital. La hoja de ruta en la que el lector es el eslabón fundamental. Razón y Palabra, 81. http://www.razonypalabra.org.mx/N/N81/V81/28_Goyanes_V81.pdf

Grimme, C., Preuss, M., Takes, F.W. y Waldherr, A. (2019). Disinformation in Open Online Media. En First Multidisciplinary International Symposium, MISDOOM 2019. Hamburg, Germany, February 27 – March 1, 2019. https://link.springer.com/book/10.1007/978-3-030-39627-5 DOI: https://doi.org/10.1007/978-3-030-39627-5

Gutiérrez Martín, A., Torrego González, A. y Vicente Mariño, M. (2019). Media education with the monetization of YouTube: the loss of truth as an exchange value / Educación mediática frente a la monetización en YouTube: la pérdida de la verdad como valor de cambio. Cultura y Educación, 31(2), 267-295. https://doi.org/10.1080/11356405.2019.1597443 DOI: https://doi.org/10.1080/11356405.2019.1597443

Hernández Conde, M. y Fernández García, M. (2019). Partidos emergentes de la ultraderecha: ¿fake news, fake outsiders? Vox y la web Caso Aislado en las elecciones andaluzas de 2018. Teknokultura. Revista de Cultura Digital y Movimientos Sociales, 16(1), 33-53. DOI: https://doi.org/10.5209/TEKN.63113

Holbrook, E., Kaur, G., Bond, J., Imbriani, J., Nsoesie, E., y Grant, C. (2016). Tweet Geolocation Error Estimation. En International Conference on GIScience Short Paper Proceedings, 1. Montreal, Canada, 27 – 30 Septiembre, 2016. https://doi.org/10.21433/b3110wf6w9p9 DOI: https://doi.org/10.21433/B3110WF6W9P9

Hu, Y. (2006). Efficient, High-Quality Force-Directed Graph Drawing. The Mathematica Journal, 10(1), 37-71. https://cutt.ly/VyDIfpR

Iyengar, S., Hahn K. S. (2009). Red media, blue media: evidence of ideological selectivity in media use. Journal of Communication, 59(1), 19-39. DOI: https://doi.org/10.1111/j.1460-2466.2008.01402.x

Jockers, M. (2017). Syuzhet, extracts sentiment and sentiment-derived plot arcs from text. https://www.rdocumentation.org/packages/syuzhet/versions/1.0.4

Kawchuk, G., Hartvigsen, J., Harsted, S., Glissmann Nim, C. y Nyirö, L. (2020). Misinformation about spinal manipulation and boosting immunity: an analysis of Twitter activity during the COVID-19 crisis. Chiropractic Manual Therapies, 28 (34). https://doi.org/10.1186/s12998-020-00319-4 DOI: https://doi.org/10.1186/s12998-020-00319-4

Kearney, M.W. (2018). Tweetbotornot: An R package for classifying Twitter accounts as bot or not. https://github.com/mkearney/tweetbotornot

Kearney, M.W. (2019). Rtweet: Collecting and analyzing Twitter data. Journal of Open Source Software, 4(42), 1829. https://doi.org/10.21105/joss.01829 DOI: https://doi.org/10.21105/joss.01829

Kessling, P. y Grimme, C. (2019). Analysis of Account Engagement in Onsetting Twitter Message Cascades. En First Multidisciplinary International Symposium, MISDOOM 2019. Hamburg, Germany, Febrero 27 – Marzo 1, 2019. https://link.springer.com/book/10.1007/978-3-030-39627-5

Kilgo, D. K, Yoo, J. y Johnson, T. J. (2019). Spreading Ebola Panic: Newspaper and Social Media Coverage of the 2014 Ebola Health Crisis. Health Communication, 34(8), 811-817. https://doi.org/10.1080/10410236.2018.1437524 DOI: https://doi.org/10.1080/10410236.2018.1437524

Klinger, U. y Svensson, J. (2015). The emergence of network media logic in political communication: A theoretical approach. New Media & Society, 17(8), 1.241-1.257. https://doi.org/10.1177/1461444814522952 DOI: https://doi.org/10.1177/1461444814522952

Levi, S. (2019). #FakeYou, fake news y desinformación. Barcelona, España: Rayo Verde Ed.

Lopez Pan, F. y Rodríguez Rodríguez, J.M. (2020). El Fact Checking en España. Plataformas, prácticas y rasgos distintivos. Estudios Sobre El Mensaje Periodístico, 26(3), 1045-1065. https://doi.org/10.5209/esmp.65246 DOI: https://doi.org/10.5209/esmp.65246

Martin, S., Brown, W., Klavans, R. y Boyack, K. (2011). OpenOrd: An Open-Source Toolbox for Large Graph Layout. En Proc. SPIE, Visualization and Data Analysis 2011, 7868. https://doi.org/10.1117/12.871402. DOI: https://doi.org/10.1117/12.871402

Meel, P. y Vishwakarma, D. K. (2019). Fake News, Rumor, Information Pollution in Social Media and Web: A Contemporary Survey of State-of-the-arts, Challenges and Opportunities. Expert Systems with Applications, 112986. https://doi.org/10.1016/j.eswa.2019.112986 DOI: https://doi.org/10.1016/j.eswa.2019.112986

Mohammad, S. y Turney, P. (2010). Emotions Evoked by Common Words and Phrases: Using Mechanical Turk to Create an Emotion Lexicon. En Proceedings of the NAACL-HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text. June 2010. LA: California.

Mohammad, S. y Turney, P. (2013). Crowdsourcing a Word-Emotion Association Lexicon. Computational Intelligence, 29(3), 436-465. https://doi.org/10.1111/j.1467-8640.2012.00460.x DOI: https://doi.org/10.1111/j.1467-8640.2012.00460.x

Mourão, R.R. y Robertson, C.T. (2019): Fake News as Discursive Integration: An Analysis of Sites That Publish False, Misleading, Hyperpartisan and Sensational Information. Journalism Studies, 20(14), 2077-2095. https://doi.org/10.1080/1461670X.2019.1566871 DOI: https://doi.org/10.1080/1461670X.2019.1566871

Murolo, N.L. (2012). Nuevas pantallas: un desarrollo conceptual. Razón y Palabra, 16(1_80), 555-565.

Nielsen, R. K. y Ganter S. A. (2017). Dealing with Digital Intermediaries: A Case Study of the Relations between Publishers and Platforms. New Media & Society, 20(4), 1600-1617. https://doi.org/10.1177/1461444817701318 DOI: https://doi.org/10.1177/1461444817701318

Oltmann, S.M., Cooper, T.B. y Proferes, N. (2020). How Twitter's affordances empower dissent and information dissemination: An exploratory study of the rogue and alt government agency Twitter accounts. Government Information Quarterly, 37(3), 101475. https://doi.org/10.1016/j.giq.2020.101475 DOI: https://doi.org/10.1016/j.giq.2020.101475

Padilla Herrada, M.-S. (2016). Marcadores y partículas discursivas interactivas en el entorno político/periodístico de Twitter. Philologia Hispalensis, Revista de Estudios Lingüisticos y Literarios, 30(1), 193-212. https://doi.org/10.12795/PH.2016.i30.10 DOI: https://doi.org/10.12795/PH.2016.i30.10

Pariser, E. (2011). The Filter Bubble. Londres, Reino Unido: Penguin Books. DOI: https://doi.org/10.3139/9783446431164

Parra-Valero, P., Rubio-Jordán, A.-V. (2020). Utilización de prensa nativa digital en las universidades españolas: causas de su reducida presencia. Profesional de la información, 29(5), e290526. https://doi.org/10.3145/epi.2020.sep.26 DOI: https://doi.org/10.3145/epi.2020.sep.26

Peinado, F. y Muela, D. (2018, 23 de mayo). El negocio de la manipulación digital en España. El País. https://bit.ly/2URouly

Peterson, T. (2018). The New York Times has folded its programmatic sales team into its larger ad sales org. Digital Day. https://digiday.com/media/new-york-times-folded-programmatic-sales-team-larger-ad-sales-org/

Ramírez, V. y Castellón, J. (2018). ‘Caso Aislado’, el fabricante español de ‘fake news’ vinculado a VOX. La Sexta. https://bit.ly/3f1aMDA

Rosenberg, H., Syed, S. y Rezaie, S. (2020). The twitter pandemic: The critical role of twitter in the dissemination of medical information and misinformation during the COVID-19 Pandemic. Canadian Journal of Emergency Medicine, 22(4), 418-421. https://doi.org/10.1017/cem.2020.361 DOI: https://doi.org/10.1017/cem.2020.361

Salaverría, R., Buslón, N., López-Pan, F., León, B., López-Goñi, I. y Erviti, M.-C. (2020). Desinformación en tiempos de pandemia: tipología de los bulos sobre la Covid-19. El profesional de la información, 29(3), e290315. https://doi.org/10.3145/epi.2020.may.15 DOI: https://doi.org/10.3145/epi.2020.may.15

Salaverría, R., Martínez-Costa, M.P., Breiner, J.G., Negredo Bruna, S., Negreira Rey, M.C., Jimeno, M.A. (2019). El mapa de los cibermedios en España. En Toural-Bran, C. López-García, X. (Eds.), Ecosistema de los cibermedios en España: tipologías, iniciativas, tendencias narrativas y desafíos.Salamanca: Comunicación Social Ediciones y Publicaciones. https://doi.org/10.52495/c1.emcs.3.p73 DOI: https://doi.org/10.52495/c1.emcs.3.p73

Sarabia, D. (28 de octubre de 2019). Los periodistas 'fake' de Periodista Digital: identidad falsa, foto sacada de Internet y currículum inventado. Eldiario.es. https://bit.ly/3zDB86h

Schulz, A. (2018). Where populist citizens get the news: An investigation of news audience polarization along populist attitudes in 11 countries. Communication Monographs, 86(1), 88-111. https://doi.org/10.1080/03637751.2018.1508876 DOI: https://doi.org/10.1080/03637751.2018.1508876

Sell, T.K., Hosangadi, D. y Trtochaud, M. (2020). Misinformation and the US Ebola communication crisis: analyzing the veracity and content of social media messages related to a fear-inducing infectious disease outbreak. BMC Public Health, 20, 550. https://doi.org/10.1186/s12889-020-08697-3 DOI: https://doi.org/10.1186/s12889-020-08697-3

Spohr, D. (2017). Fake news and ideological polarization. Business Information Review, 34(3), 150–160. https://doi.org/10.1177/0266382117722446 DOI: https://doi.org/10.1177/0266382117722446

Sundar, S. S. (2008). The MAIN Model: A Heuristic Approach to Understanding Technology Effects on Credibility. En Metzger M. J. y Flanagin, A. J (Eds.), Digital Media, Youth, and Credibility, 73-100. Cambridge, MA: The MIT Press.

Tandoc, E. C., Lim, Z. W. y Ling, R. (2017). Defining “Fake News”. Digital Journalism, 6(2), 137–153. DOI: https://doi.org/10.1080/21670811.2017.1360143

Urman, A. (2019). Context matters: political polarization on Twitter from a comparative perspective. Media, Culture & Society, 016344371987654. https://doi.org/10.1177/0163443719876541 DOI: https://doi.org/10.1177/0163443719876541

Van der Veen, H., Hiemstra, D., Van den Broek, T., Ehrenhard, M. y Need, A. (2015). Determine the User Country of a Tweet. Social and Information Networks. https://arxiv.org/abs/1508.02483

Vila Márquez, F. y Arce García, S. (2019). Fake News y difusión en Twitter: el caso de Curro, el perro “condenado”. Historia y Comunicación Social, 24(2), 485-503. https://doi.org/10.5209/hics.66292 DOI: https://doi.org/10.5209/hics.66292

Vraga, E. K.;, Bode, L. y Tully, M. (2020). Creating News Literacy Messages to Enhance Expert Corrections of Misinformation on Twitter. Communication Research, 009365021989809. https://doi.org/10.1177/0093650219898094 DOI: https://doi.org/10.1177/0093650219898094

Walter, D., Ophir, Y. y Jamieson, K. H. (2020). Russian Twitter Accounts and the Partisan Polarization of Vaccine Discourse, 2015–2017. American Journal of Public Health, 110, 718-724. https://doi.org/10.2105/ajph.2019.305564 DOI: https://doi.org/10.2105/AJPH.2019.305564

Wissman, B. (2 de marzo 2018). Micro-Influencers: The Marketing Force of The Future?. Forbes. https://bit.ly/3iV9xXN.

Xu, Q., Chen, S. y Safarnejad, L. (2020): Effects of Information Veracity and Message Frames on Information Dissemination: A Case Study of 2016 Zika Epidemic Discussion on Twitter. Health Communication. https://doi.org/10.1080/10410236.2020.1773705 DOI: https://doi.org/10.1080/10410236.2020.1773705

Zannettou, S., Sirivianos, M., Blackburn, J. y Kourtellis, N. (2019). The Web of False Information. Journal of Data and Information Quality, 11(3), 1–37. https://doi.org/10.1145/3309699 DOI: https://doi.org/10.1145/3309699

Zola, P., Ragno, C. y Cortez, P. (2020). A Google Trends spatial clustering approach for a worldwide Twitter user geolocation. Information Processing & Management, 57(6), 102312. https://doi.org/10.1016/j.ipm.2020.102312 DOI: https://doi.org/10.1016/j.ipm.2020.102312

Published

13/09/2021

How to Cite

Arce García, S., Vila Márquez, F., & Fondevila i Gascón, J. F. (2021). Polarization on Twitter during the COVID-19 crisis: Caso Aislado and Periodista Digital. Revista De Comunicación, 20(2), 29–47. https://doi.org/10.26441/RC20.2-2021-A2

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